Hidradenitis suppurativa and cardiovascular diseases: A bidirectional Mendelian randomization study

Abstract Background Prior investigation has indicated a link between Hidradenitis suppurativa (HS) and cardiovascular diseases (CVDs), yet the causal relationship (CR) between these conditions remains unresolved. Methods This investigation utilized bidirectional Mendelian randomization (MR) analysis to determine the CR between HS and CVDs. Genetic instruments for both conditions were sourced from genome‐wide association studies (GWAS). The GWAS summary data for CVD comprised coronary artery disease (CAD), myocardial infarction (MI), coronary atherosclerosis (CA), ischemic stroke (IS), and chronic heart failure (CHF). Four new approaches were added to the inverse variance weighted (IVW) method for the main analysis: weighted median, weighted MR‐Egger, simple mode, and weighted mode. The validity of the causal conclusions was verified by sensitivity tests that included leave‐one‐out analysis, heterogeneity, and pleiotropy. Results HS and CAD (OR = 1.024; 95%CI: 1.002–1.046, P = 0.033), MI (OR = 1.001; 95%CI: 1.000–1.002, P = 0.033), and CA (OR = 1.001; 95%CI: 1.000–1.002, P = 0.022) were identified to have a positive CR, according to the IVW analysis. Conversely, no significant association was identified between HS and either IS or CHF. Furthermore, the bidirectional analysis indicated no reverse causation between these diseases. Conclusion The findings of this study suggest a potential CR between HS and CAD, MI, and CA. Additional research is warranted to elucidate the biological mechanisms underlying these associations.


Study design
To explore the possible CR linking HS and CVDs, we employed MR analysis.In this approach, HS was considered the exposure variable, and single nucleotide polymorphisms (SNPs) strongly linked to HS were utilized as instrumental variables (IVs).The outcomes of interest encompassed five distinct CVD: coronary artery disease (CAD), myocardial infarction (MI), coronary atherosclerosis (CA), ischemic stroke (IS), and chronic heart failure (CHF).Subsequently, the roles of exposure and outcome data were reversed for a bidirectional analysis.This study adhered to three key assumptions: ① IVs should be highly correlated with exposure; ② IVs should not be influenced by variables that may potentially confuse the relationship between exposure and outcome; and ③ IVs should only affect the outcome as a direct result of exposure, without other pathways.The analytical procedure is depicted in Figure 1.

Data sources
The HS GWA dataset was sourced from the latest and most comprehensive FinnGen R10 version, encompassing 1,070 cases and 394,105 controls of European ancestry.Data for CVDs were obtained from the IEU OpenGWAS project.No further ethical approval was needed because all of the data utilized in this analysis are publicly available.
Table 1 presents comprehensive details about the datasets.

Instrument selection
To minimize potential bias from strong linkage disequilibrium between SNPs, rigorous screening criteria were applied: ① For HS as the exposure, SNPs with a significance level of P < 5 × 10 −6 were utilized; for CVDs as the exposure, the threshold was P < 5 × 10 , where N is the sample size of the exposure, K is the number of SNPs; R 2 is the proportion of variance explained by IVs; 8][19] ⑤ To further minimize confounding, LDlink (https://ldlink.nih.gov/?tab = home) was used to exclude IVs associated with confounding factors. 20

MR analysis
This study included five different techniques: inverse variance weighted (IVW), MR-Egger regression, weighted median, simple mode, and weighted mode, to ascertain CRs.The IVW method determines the weighted average of the effect sizes of all IVs during the analysis, providing relatively reliable results. 21Consequently, IVW results were selected as the primary indicator for assessing causal effects, while other methods were employed for supplementary evaluation.
The outcomes are provided as 95% confidence intervals (CIs) and odds ratios (ORs), with P < 0.05 being employed to indicate statistical significance.The false discovery rate (FDR) for multiple testing was controlled utilizing the Benjamini-Hochberg approach in light of the numerous MR studies that were performed. 22If P < FDR < 0.05, the  [24][25][26] Radial MR was used to identify and eliminate outliers. 27The robustness of the results was tested by progressively deleting each and every IV utilizing the leave-one-out strategy to identify the impact of specific SNPs on MR results. 28e analyses were primarily conducted utilizing R software (version

IVs
When utilizing HS as the exposure and CVD as the outcome, 16 SNPs were initially identified as IVs based on the established criteria.
However, rs4713570 and rs7975017 were excluded due to their association with BMI, a known high-risk factor for CVDs.For the reverse analysis, with CVDs as the exposure and HS as the outcome, the

Causal effect of HS on CVDs
HS was linked to a higher risk of CAD, according to IVW analysis  2A).The results are shown in Table S11.These findings suggest that genetic predisposition to CVDs does not markedly influence the development of HS.The results are shown in Table S12.

Sensitivity analysis of MR
The sensitivity analysis included tests for pleiotropy, heterogeneity, and leave-one-out analysis.In the MR-Egger regression, there was no evidence of horizontal pleiotropy (intercept P > 0.05).Furthermore, both IVW and MR-Egger analyses indicated no heterogeneity (Table 2).
The leave-one-out analysis showed that the overall findings were not driven by any single SNP (Figure S1).The funnel plot (Figure S2) also visually confirmed the absence of heterogeneity in the analyzed data.

DISCUSSION
This investigation is the initial attempt to utilize GWAS summary data to evaluate the CR between HS and CVDs.The analysis included five common CVDs: CAD, MI, CA, IS, and CHF.The MR analysis provided three key insights.Firstly, a suggestive positive CR was observed between HS and CAD, MI, and CA, indicating that HS may elevate the risk of developing these conditions.Secondly, no marked CR was identified between HS and either IS or CHF.Thirdly, the presence of CVDs did not correlate with an increased incidence of HS.
0][31][32][33] For instance, Reddy et al. 34 found that, compared with non-HS patients, those with HS had a 21% increased risk of MI after adjusting for relevant cardiovascular risk factors.A cohort study in Taiwan, which included 478 newly diagnosed patients with HS and 1,912 controls, also found that individuals with HS had a higher risk of suffering from CAD after adjusting for confounding factors (aHR: 2.722; 95% CI: 1.628-4.553;P < 0.001). 35Additionally, patients with HS exhibited an increased incidence of subclinical atherosclerosis compared to healthy controls. 36,37 is an immune-mediated chronic inflammatory disease, and its inflammatory effects extend beyond the skin.The systemic inflammation resulting from the interaction of inflammatory factors and immune cells may contribute to an elevated cardiovascular risk. 38Blood tests in patients with HS have shown increased levels of cytokines IL-1β and IL-6, which can induce the liver to produce serum amyloid A, thereby increasing the risk of atherosclerosis. 39Research has also found that IL-32 is overexpressed in both the lesional skin and serum of patients with HS. 40 In addition to triggering pro-inflammatory cytokines, including IL-6, IL-1β, and TNFα, IL-32 can lead to endothelial dysfunction and reduce blood levels of high-density lipoprotein, which increases the risk of developing CVD. 41It has been observed that HS patients with an inflammatory phenotype and higher C-reactive protein levels are linked to an increased cardiovascular risk. 42Moreover, a new study has identified Trimethylamine N-Oxide (TMAO) as a novel predictor of clinical severity in individuals with HS, showing a positive correlation with disease severity. 43Interestingly, TMAO can bind to protein kinase R-like endoplasmic reticulum kinase to induce the transcription factor FoxO1, promoting cardiac metabolic diseases. 44Long-term elevation of TMAO levels is linked to a higher risk of CVD. 45 Given these findings, it is hypothesized that inflammatory factors may mediate the CR between HS and cardiovascular risk.
The merit of this study is its extensive MR analysis that reduces confounding factor interference by using data from public databases.
The findings' dependability is further supported by the sensitivity and heterogeneity analysis.However, several limitations must be acknowledged.First, the data sources are predominantly from the European population; therefore, attention should be paid to extrapolating the results to other ethnicities.Second, while the results were adjusted for multiple testing, the outcomes tend to be more conservative due to the relatively modest impact of HS on these diseases.Larger sample numbers or more reliable genetic instrumental factors could be needed for validation in further research.Third, the absence of detailed demographic information and clinical characteristics of the participants precluded subgroup analyses.Lastly, this study did not investigate the potential mechanistic pathways that may mediate the observed associations.Further investigation is warranted to identify the relationship between HS, CVDs, and inflammatory factors, as shared inflammatory factors between the two conditions may become critical therapeutic targets for preventing these diseases and their complications.

CONCLUSION
This study elucidated the genetic impact of HS on common CVDs.It identified a potential CR between HS and CAD, MI, and CA, indicating a possible link between HS and these CVDs.Clinicians treating patients with HS should consider not only the management of skin symptoms but also be vigilant about this potential risk to mitigate complications and reduce mortality.

− 8 .
② SNPs in linkage disequilibrium among the selected IVs were eliminated, with thresholds set at r 2 < 0.001 and kb = 10000.③ Relevant information for the selected IVs was retrieved from the GWAS data of the outcome, with allele alignment performed and palindromic sequences with intermediate allele frequencies removed.④ Weak IVs were eliminated by calculating each SNP's F-value; SNPs with an F-value < 10 indicated weak IVs and were eliminated.The formula for calculating the F-value is F = R 2 ×(N−K−1)
Source of the GWAS data.
1 Bidirectional two-sample Mendelian randomization study workflow to comprehensively investigate the causal relationship between hidradenitis suppurativa and cardiovascular diseases.IVW, inverse variance weighted; SNPs single nucleotide polymorphisms.TA B L E 1 Various techniques were employed to identify the presence of heterogeneity and pleiotropy.Cochran's Q statistic assessed heterogeneity among IVs in the IVW and MR-Egger methods.Pleiotropy was identified utilizing the MR-PRESSO test for the intercept term of the MR-Egger regression; a P > 0.05 result revealed the lack of both pleiotropy and heterogeneity.